Join EY's Digital Engineering team as a Technical Lead, specializing in Agentic AI and Python development. This role offers a unique opportunity to shape the future of financial services technology, leveraging cutting-edge AI and full-stack development practices. You will be instrumental in delivering innovative solutions and mentoring a high-performing technical team within a globally recognized professional services organization.

EY Digital Engineering is at the forefront of digital transformation, partnering with clients to address their most critical challenges in business strategy, customer engagement, and technology innovation. We provide integrated advisory and execution services, enabling clients to achieve sustainable competitive advantage and navigate rapid market changes. This is your chance to be part of an exceptional career journey and contribute to building a better working world.

As a Technical Lead, you will spearhead product design and drive hands-on development, ensuring efficient and optimized source code that aligns with functional specifications. You'll challenge existing tech stacks and API choices, embracing industry best practices to balance time-to-market with product quality.

Your technical leadership will involve demonstrating best practices in all software development facets, including front-end, back-end, APIs, data layers, third-party integrations, and AI models. You will map functional requirements to product features, ensuring comprehensive coverage and accuracy. Critical thinking, strong communication, and logical reasoning are essential for technical discussions and decision-making. Additionally, you'll perform techno-functional testing, automate testing processes where feasible, and collaborate with architects and application teams for secure solution delivery.

We are seeking a Technical Lead with 8-14 years of robust experience in technical source code development, encompassing design leadership and hands-on application. A strong background in full-stack engineering, including Python-led back-end development with frameworks like Django or FastAPI, microservices, and data integration, is crucial.

Deep expertise in AI engineering, design, and adoption, including Vector DBs, Python AI frameworks, RAG models, LLMs/SLMs, and agentic AI integration, is required. Proficiency in cloud infrastructure deployment (Azure, AWS, GCP) and CI/CD pipelines, along with version control (Git), is essential. Experience with Python-driven Machine Learning model implementation (ML Ops) and AI model ops is also necessary. Familiarity with databases like PostgreSQL or MongoDB is expected.

A Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent practical experience, is required. While not mandatory, certifications in cloud platforms (preferably Azure) or AI/ML, along with prior working experience in the Risk domain, are considered advantageous.